The effect of diet and feeding level on survival and weight gain of hand‐raised harbor seal pups (<i>Phoca vitulina</i>)
Bibliographic record
Abstract
Hundreds of stranded harbor seals pups (Phoca vitulina) are brought to wildlife rescue centers every year. Typical hand-rearing diets include artificial milk-replacers and diets based on macerated fish fed via gavage, but weight gains are often low and mortality rates can be high. This study compared survival and weight gain of orphaned seal pups fed either artificial milk-replacer or fish-formula. Pups admitted to the facility in summer 2007 (n=145) and 2008 (n=98) were randomly assigned to one of two diets and fed by gavage until weaning. In 2007, pups fed milk-replacer gained more (43 ± 12 g/d) than those fed fish-formula (loss of 13 ± 6 g/d; P<0.002). In 2008, when intake was increased from 8 to 11% of body weight daily, weight gain improved for both diets but remained higher in pups fed milk-replacer (123 ± 12 g/d, vs. loss of 6 ± 8 g/day; P<0.001). Pup survival to weaning was significantly higher in 2008 than 2007 (P<0.001) and was higher for pups on milk-replacer compared with those on fish-formula (P<0.05). Survival was also correlated with body weight at admittance (P<0.001). Although neither diet achieved the weight gains recorded in mother-raised pups (400-800 g/d), the artificial milk-replacer was clearly more successful, and pups fared better in the second year of the study when intake was higher.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".